Austrian Agency Automates Sound Propagation Modeling

The cost and time associated with manually assembling and processing detailed image data is significant. Integrating three-dimensional data, such as that generated by aerial laser scanning, vastly improves the value and accuracy of the information product produced; however, this data is practically impossible to manually prepare and analyze. Only by using software to automate data handling and analysis is it feasible for organizations to tackle land-use modeling and mapping projects for large areas. GEOinfo did exactly this when it adopted a process capable of automatically analyzing large volumes of data to deliver accurate and reproducible results in a standardized manner.

GEOinfo — the Department of Surveying and Geo Information of the State Government of Lower Austria — is the major provider of geographic data in the region. The department is structured into three areas: topographical survey, data collection, and data processing. GEOinfo's portfolio includes digital data and secondary products, such as maps and graphics, which are created on behalf of the state government.

Sound-wave propagation models for traffic noise have been generated over an area of more than 20,000 square kilometers in Austria using Trimble INPHO and eCognition software. The project detects and quantifies changes in forests, buildings, and water bodies using aerial laser scanning and orthophotos, and has been developed by the Government of Lower Austria as part of an urban planning initiative from the European Union. With measured accuracy ratings above 94%, the automated approach provides an information product that would be completely unviable and cost-prohibitive to create manually.

Handling Airborne Geospatial Data

In the GEOinfo project, automation of photogrammetric processes and digital terrain model (DTM) generation was essential due in part to the large data volume. Project personnel used INPHO, a photogrammetry and digital terrain modeling software suite, to manage and process GEOinfo's aerial laser scanning data over large areas.

The TopDM module was used to manage approximately 30,000 raw data flight strips, from which 20,000 DTM and 20,000 digital surface model (DSM) data tiles were derived. Various SCOP++ modules were applied to these data sets to perform tasks such as point cloud classification using filtering strategies, shade calculation, slope calculation, profile tools, and other terrain algebra methods. Available breaklines were used during these processes to increase the quality of the terrain modeling, especially in challenging topographic areas. The output of these processes provides input data for the next workflow step: the production of value-added products using eCognition.

Detecting and Quantifying Changes

GEOinfo used eCognition image analysis software to detect and quantify changes in forests, buildings, fields, and water areas from the DSMs, DTMs, and orthophotos. Within eCognition, a variety of source data can be imported, fused, and segmented to create meaningful objects using prescribed conditions such as average elevation and normalized differenced vegetation index. The software identifies objects and makes contextual inferences, using the color, shape, texture, and size of objects, as well as spatial relationships.

This logic was applied to data representing 20,000 square kilometers of Lower Austria. To deal with this volume of data, a tiling and stitching technique was applied, creating 2000 x 2000–pixel tiles each representing 1 square kilometer of territory. Within each tile, eCognition automatically classified elevated objects and distinguished buildings, trees, scrubs, and sealed areas. Results were then stitched together and border effects removed to create the final information product for import into ESRI ArcGIS.

Project Outcome

The analysis of an area of this size requires large amounts of data to be processed in a timely and cost-efficient manner. Replacing manual analysis routines with an automated software-assisted approach, it was feasible to develop land-use models for very large areas without a large amount of resources. Where manual analysis of one building might cost 2–4 Euros, the automated approach costs only 0.1–0.2 Euros.

An accuracy assessment of the resulting shape files showed that built-up and forested areas were correctly classified for 94.3% and 96.1% of the area, respectively. With high levels of accuracy achieved at a low cost, the project was deemed to be successful and additional iterations are planned for each of the next four years.

"INPHO software allowed us to produce robust terrain models with virtually no manual interaction, enabling us to produce and manage digital terrains in a cost-efficient, standardized, and automated manner," said Michael Pregesbauer, deputy department head at GEOinfo. "eCognition allowed us to concurrently analyze both the digital imagery and terrain models reliably, extracting the land-cover and land-use information we were seeking."

About the Author: Todd Taylor

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